This section is intended to introduce various aspects of the art, which may be associated with exemplary embodiments of the present invention. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the present invention. Accordingly, it should be understood that this section should be read in this light, and not necessarily as admissions of prior art.
Seismic data are acquired and processed to help geoscientists visualize and quantify key metrics linked to detecting or assessing the quantity and quality of hydrocarbons potentially present in the subsurface. Seismic datasets are a way to “image” the subsurface geological layers in a way that geoscientists can interpret geological layers and morphologies. Geological layers are characterized by their rock physical, acoustical properties, direction of deposition or continuity, but also by their “structure”: direction towards which layers are dipping toward at the current time. The “structure” is characterized by two principal measurements called dip and azimuth that define the exact direction layers are dipping towards in the subsurface. These measurements define the dip and strike direction for any point in the subsurface.
FIG. 1 illustrates dip and strike directions. The strike direction of a geological planar feature 100 is a line 102 representing the intersection of that feature 100 with a horizontal plane 104. The strike direction is usually referred to as the “azimuth” or angle, in a horizontal plane, between the strike line 102 and a reference direction (i.e., north or a specified direction like the survey main axis). The dip vector feature 106 is vector which has the steepest angle (relative to the horizontal plane 104) of descent within the same planar feature 100 Dip and strike directions are perpendicular to one another. The dip vector is characterized by its dip and also its dip azimuth which is the direction the dip vector points towards. The dip vector azimuth is 90 degrees rotated compared to the “azimuth” of the planar feature 100. In this paper, the “dip direction” is the direction the dip vector is pointing towards and the “strike direction” is the horizontal vector feature 102.
The third direction commonly used is the normal to the geological layer and is defined by the vector perpendicular to the plane defined by the dip and strike vectors (i.e. planar feature 100). FIG. 2 illustrates a normal vector to a given surface (from Oleg Alexandrov, 2011). For a given surface, the strike and dip direction define a dip-azimuth plane 200. The normal vector 202 to the surface 204 is the vector perpendicular to the dip-azimuth plane 200.
Extracting valuable information from seismic data, especially three-dimensional (3D) seismic data, can be based on algorithms (or mathematical operations) that use operators in XYZ space. An operator is a way to select in the XYZ or INLINE/CROSSLINE/Z seismic sample points to run operations on.
A classic way of extracting information from seismic data is to use structure guided image processing applied to seismic data. The structure dip and strike directions can be computed in several ways resulting in dip and azimuth data cubes of the same footprint as the seismic data they are computed on (FIG. 1). In order to better relate seismic data measurements to geology, the classic approach in operator design is to use a structure guided operator; namely “dip-steered” or “strike-steered” operator.
The current standard in the industry is to use dip and azimuth (FIGS. 1 and 2) to guide the operator direction in two fashions. The first, for a large operator, the operator direction is either kept constant, inheriting a single dip and azimuth from the computation location for the entire operator (FIGS. 5 and 7). The operator is called “Linear” or local because it uses a unique direction computed at the center of the operator. The major flaw with these approaches is that the lateral variation of dip and strike directions are not fully taken into account. The second is using a cascaded approach where a small operator is run on the data multiple times, recursively, with each iteration's result becoming the input for the next iteration. The cascaded approach fully utilizes the lateral variation of dip and strike, generating the results of a larger operator without the requirement of explicitly populating the larger operator, but requires running multiple times.
For conventional methods, the resulting data point selection by the operator may include data points that are not intended to be selected or miss relevant others.
A technical problem exists in regards to how to properly design the operator using dip and strike direction data to have a meaningful operation result. Trying to select data points in the strike or dip direction would requires an operator that changes direction as it expands away from the central computation location, because dip and strike direction are not the same from point to point. This has not been previously done in the industry.
Further background information can be found in Nonlinear structure-enhancing filtering using plane-wave prediction, Liu et al., Geophysical Prospecting, 2010, 58, 415-427; and Structure-oriented smoothing and semblance, Hale, Center for Wave Phenomena, Colorado School of Mines.